Evaluation of Quantification Methods to Compensate for Matrix Effects in the Analysis of Benzalkonium Chloride and Didecyldimethylammonium Chloride in Fruits and Vegetables by LC-ESI-MS/MS

Given the extensive presence of some toxic quaternary ammonium compound residues in foodstuffs arriving into the EU during 2012, the Food Authority Control of Geneva decided to implement a monitoring plan to investigate the presence of these contaminants in food: a method based on quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction and liquid chromatography electrospray tandem mass spectrometry was developed for analyzing didecyldimethylammonium chloride and four benzalkonium chloride homologue residues in fruits and vegetables. An in-house method validation, based on the SANCO guidelines (Document SANCO No. 12571/2013), was conducted using three independent series in orange, lettuce, and avocado composite samples spiked at three levels (10, 100, 500 μg/kg). Trueness and precision were calculated by pooling all results at each concentration level to account for the variability among fruits and vegetables. To avoidmatrix effects on quantitative results, five quantification strategies were investigated: (i)solvent calibration, (ii) matrix-matched calibration prepared on samples and (iii) on sample extract aliquots, and (iv) standard addition prepared on samples and (v) on sample extract aliquots. Due to the nonlinear instrumental response for the large concentration range investigated, a quadratic calibration model was mandatory for all approaches. Solvent calibration gave very poor recoveries due to the high signal suppression caused by matrix effects. Smaller biases were observed for matrix-matched calibrations; however, these results exhibited relatively low precision. Both of the standard addition methods compensated for matrix effects and provided accurate analytical results. Due to the ease of its implementation, the matrix standard addition method, where analytes are added to sample extract aliquots, was preferred over the classical standard addition in samples. Nonlinear extrapolations appeared to be particularly effective in obtaining good results for both standard addition methods when the calibration curve was convex or very slightly concave. The resulting validated method was used to monitor 108 fruit and vegetable commercial samples in May 2013.